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@article{182623,
        author = {ASHA R},
        title = {A Systematic Assessment of Chest X-Ray Analysis and Improvements for Pneumonia Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {2963-2973},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182623},
        abstract = {The Pneumonia is an acute respiratory disease that occurs in the lungs. They include similarities between symptoms of viral and bacterial pneumonia. The disease is hard to diagnose, as the methods based on polymerase chain reaction, the most reliable ones, give results in several hours only, whereas they presuppose strict demands regarding observing the demands of the analysis technology and professionalism of the staff. This article suggested concatenated CNN model in recognising pneumonia with an image enhancing using fuzzy logics. The image enhance cement mechanism of fuzzy logic as proposed to new algorithms to extract the high accuracy pneumonia detection by deep learning approaches for the larger extended to capture the high precision quality of CRX images to analyses the pneumonia causes. The various datasets and key statistics helps to prevent the affecting of pneumonia attack. The algorithm was trained by means of four datasets, equipped with original and enhanced images that employed fuzzy entropy, standard deviation as well as histogram equalization. It was also shown that the upgraded datasets were able to significantly improve the performance of the CCNN and the fuzzy entropy-added dataset recorded the best performance.},
        keywords = {CRX images, Pneumonia detection, Fuzzy algothrims, CNN models;},
        month = {July},
        }